Dynamic learning and resource management under uncertainties for smart grid and cognitive radio networks

University of Minnesota Ph.D. dissertation. May 2014. Major: Electrical/Computer Engineering. Advisor: Georgios B. Giannakis. 1 computer file (PDF); xi, 101 pages.The importance of timely applications and decisions in dynamic environments, has led to the integration of intelligent networks to increase efficiency and end-user satisfaction in various application domains including telecommunication and power grid networks. Contemporary intelligent networks require advanced statistical signal processing and optimization tools to learn, infer and control their operation. This integration poses new challenges and has witnessed the emergence of novel resource management and learning techniques to cope with dynamics. In addition, in order to have implementable resource management algorithms, it is crucial to model the underlying sources of uncertainty in the optimization framework. This thesis develops algorithms for resource allocation under channel uncertainty in cognitive radio (CR) communication networks and contributes to demand coordination under uncertainty in power networks.Demand coordination through real-time pricing is addressed first by capitalizing on the uncertainty involved in the consumption behavior of consumers. Prerequisite to the demand coordination task is learning the uncertainty present in power consumption data. The dependency of consumers' consumption behavior on the announced prices and their neighbors' behavior, is modeled through graphical models. In particular, the electric vehicle (EV) consumers are considered and the adopted model also captures dynamics of EV consumers' time-varying charging decisions. Leveraging the online convex optimization (OCO) framework, an online algorithm for tracking the model is devised. With minimal assumptions on the structure of the temporal dynamics, and while accounting for the possibly adversarial consumption behavior of consumers, the proposed online algorithm provides performance guarantees. The probability distributions obtained through the tracking algorithm are then deployed as input to stochastic economic profit maximization for real-time price setting.Learning in the presence of missing data is a pervasive problem in statistical data analysis. Next, attention is turned to tracking the dynamic charging behavior of EV consumers, when at each time slot some of the consumers' consumption decisions are possibly missing. The problem amounts to online classification with missing labels. An online algorithm is proposed to wed real-time estimation of the missing data with learning of complete data in the OCO framework.As regards CR networks, this thesis introduces novel resource allocation algorithms for orthogonal frequency-division multiple access (OFDMA) CR under channel uncertainty where the unique approaches can be fitted to a class of large-scale robust mixed-integer problems. Due to the lack of cooperation of the licensed system, CRs must resort to less efficient channel estimation techniques thus incurring an inevitable channel estimation error. It is shown that CR interference constraints under channel uncertainty can be cast as chance constraints. On the other hand, instead of just modeling the user rates by logarithmic functions of transmit-powers, justified under ideal Gaussian coding, practical finite-alphabet constellations are adopted which leads to an optimization objective of a weighted sum of mutual information. When multiple users are present, due to the combinatorial search for optimal subcarrier assignment, the problem is non-convex and hard to solve, as the optimization variables are coupled across all subcarriers. To circumvent the resulting computational hurdle, tight and conservative approximations of the chance constraint are introduced to break the coupling and enforce separability per subcarrier. The separableproblem across subcarriers opens the door to the dual decomposition approach, which leads to a near-optimal and computationally efficient solution

Network Slicing for Wireless Networks Operating in a Shared Spectrum Environment

Network slicing is a very common practice in modern computer networks. It can serve as an efficient way to distribute network resources to physical groups of users, and allows the network to provide performance guarantees in terms of the Quality of Service. Physical links are divided logically and are assigned on a per-service basis to accomplish this. Traditionally, network slicing has been done mostly in wired networks, and bringing these practices to wireless networks has only been done recently. The main contribution of this thesis is network slicing applied to wireless environments where multiple adjacent networks are forced to share the same spectrum, namely in LTE and 5G. Spectrum in the sub-6GHz range is crowded by a wide range of services, and managing interference between networks is often challenging. A modified graph coloring technique is used both as a means to identify areas of interference and overlap between two networks, as well as assign spectrum resources to each node in an efficient manner. A central entity, known as the ”Overseer”, was developed as a bridge to pass interference-related information between the two coexisting networks. Performance baselines were first gathered for network slicing in a single-network scenario, followed by the introduction of a second network and the evaluation of the efficacy of the graph coloring approach. In the cases of highest interference from the secondary network, the modified graph coloring approach provided more than 22.3% reduction in median user delay, and more than 36.0% increase in median single-user and slice-aggregate throughput across all three network slices compared to the non-graph coloring scenario

Spectrum Map and its Application in Cognitive Radio Networks

Recent measurements on radio spectrum usage have revealed the abundance of underutilized bands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access. Cognitive radio based secondary networks that utilize such unused spectrum holes in the licensed band, have been proposed as a possible solution to the spectrum crisis. The idea is to detect times when a particular licensed band is unused and use it for transmission without causing interference to the licensed user. We argue that prior knowledge about occupancy of such bands and the corresponding achievable performance metrics can potentially help secondary networks to devise effective strategies to improve utilization. In this work, we use Shepard\u27s method of interpolation to create a spectrum map that provides a spatial distribution of spectrum usage over a region of interest. It is achieved by intelligently fusing the spectrum usage reports shared by the secondary nodes at various locations. The obtained spectrum map is a continuous and differentiable 2-dimension distribution function in space. With the spectrum usage distribution known, we show how different radio spectrum and network performance metrics like channel capacity, secondary network throughput, spectral efficiency, and bit error rate can be estimated. We show the applicability of the spectrum map in solving the intra-cell channel allocation problem in centralized cognitive radio networks, such as IEEE 802.22. We propose a channel allocation scheme where the base station allocates interference free channels to the consumer premise equipments (CPE) using the spectrum map that it creates by fusing the spectrum usage information shared by some CPEs. The most suitable CPEs for information sharing are chosen on a dynamic basis using an iterative clustering algorithm. Next, we present a contention based media access control (MAC) protocol for distributed cognitive radio network. The unlicensed secondary users contend among themselves over a common control channel. Winners of the contention get to access the available channels ensuring high utilization and minimum collision with primary incumbent. Last, we propose a multi-channel, multi-hop routing protocol with secondary transmission power control. The spectrum map, created and maintained by a set of sensors, acts as the basis of finding the best route for every source destination pair. The proposed routing protocol ensures primary receiver protection and maximizes achievable link capacity. Through simulation experiments we show the correctness of the prediction model and how it can be used by secondary networks for strategic positioning of secondary transmitter-receiver pairs and selecting the best candidate channels. The simulation model mimics realistic distribution of TV stations for urban and non-urban areas. Results validate the nature and accuracy of estimation, prediction of performance metrics, and efficiency of the allocation process in an IEEE 802.22 network. Results for the proposed MAC protocol show high channel utilization with primary quality of service degradation within a tolerable limit. Performance evaluation of the proposed routing scheme reveals that it ensures primary receiver protection through secondary power control and maximizes route capacity

The information theoretic approach to signal anomaly detection for cognitive radio

Efficient utilisation and sharing of limited spectrum resources in an autonomous fashion is one of the primary goals of cognitive radio. However, decentralised spectrum sharing can lead to interference scenarios that must be detected and characterised to help achieve the other goal of cognitive radio—reliable service for the end user. Interference events can be treated as unusual and therefore anomaly detection algorithms can be applied for their detection. Two complementary algorithms based on information theoretic measures of statistical distribution divergence and information content are proposed. The first method is applicable to signals with periodic structures and is based on the analysis of Kullback-Leibler divergence. The second utilises information content analysis to detect unusual events. Results from software and hardware implementations show that the proposed algorithms are effective, simple, and capable of processing high-speed signals in real time. Additionally, neither of the algorithms require demodulation of the signal

On Enabling Concurrent Communications in Wireless Networks

Today innumerable devices use the wireless spectrum for communication, including cell-phones, WiFi devices, military radios, public safety radios, satellite phones etc. This crowding is limiting the experience of each device either through interference or by waiting fortheir turn to communicate. So, how do we allow a limited spectral resource to reliably scale to many more devices? This is possible through concurrent communication where multiple links share the spectrum and communicate simultaneously using multi-antenna techniques. One promising technique is Interference Alignment (IA), that has been shown to be Degrees-of-Freedom optimal under some conditions. Still, IA requires accurate channel knowledge to be effective and its ability to achieve high throughput under time varying wireless conditions is yet unproven. We make progress towards understanding these limitations and provide viable solutions.We study an IA system under different models of the time varying channel and derive expressions for the achieved rate over time and the system throughput. Using these, we can arrive at the optimal duration of the data phase that maximizes throughput. We proposetwo strategies that help to counter the effects of a time varying channel. First, data aided receiver beam-tracking along with link adaptation provides a sizable improvement in the received signal to interference and noise ratio. Second, updating the transmit beams during data transmission using short feedback pilots improves alignment at the receivers. In faster varying channels, we get a more stable achieved rate whereas in slower varying channels, we see additional throughput gains. The conclusion from this work is that an IA system must be trained more frequently than the channel coherence time to ensure high throughput and beam adaptation during the data phase gives significant robustness to the system.Lastly, we present an IA based medium access control (MAC) protocol that outperforms traditional protocols. Our concurrent carrier sense multiple access (CSMA) protocol based on beam-nulling is compatible with CSMA and increases the sum throughput by 2 to 3x.We also show that IA outperforms optimal time division multiple access under time varying conditions. Hence a well-designed IA system can enable reliable concurrent communications in a wireless network

Analysis and Ad-hoc Networking Solutions for Cooperative Relaying Systems

Users of mobile networks are increasingly demanding higher data rates from their service providers. To cater to this demand, various signal processing and networking algorithms have been proposed. Amongst them the multiple input multiple output (MIMO) scheme of wireless communications is one of the most promising options. However, due to certain physical restrictions, e.g., size, it is not possible for many devices to have multiple antennas on them. Also, most of the devices currently in use are single-antenna devices. Such devices can make use of the MIMO scheme by employing cooperative MIMO methods. This involves nearby nodes utilizing the antennas of each other to form virtual antenna arrays (VAAs). Nodes with limited communication ranges can further employ multi-hopping to be able to communicate with far away nodes. However, an ad-hoc communications scheme with cooperative MIMO multi-hopping can be challenging to implement because of its de-centralized nature and lack of a centralized controling entity such as a base-station. This thesis looks at methods to alleviate the problems faced by such networks.In the first part of this thesis, we look, analytically, at the relaying scheme under consideration and derive closed form expressions for certain performance measures (signal to noise ratio (SNR), symbol error rate (SER), bit error rate (BER), and capacity) for the co-located and cooperative multiple antenna schemes in different relaying configurations (amplify-and-forward and decode-and-forward) and different antenna configurations (single input single output (SISO), single input multiple output (SIMO) and MIMO). These expressions show the importance of reducing the number of hops in multi-hop communications to achieve a better performance. We can also see the impact of different antenna configurations and different transmit powers on the number of hops through these simplified expressions.We also look at the impact of synchronization errors on the cooperative MIMO communications scheme and derive a lower bound of the SINR and an expression for the BER in the high SNR regime. These expressions can help the network designers to ensure that the quality of service (QoS) is satisfied even in the worst-case scenarios. In the second part of the thesis we present some algorithms developed by us to help the set-up and functioning of cluster-based ad-hoc networks that employ cooperative relaying. We present a clustering algorithm that takes into account the battery status of nodes in order to ensure a longer network life-time. We also present a routing mechanism that is tailored for use in cooperative MIMO multi-hop relaying. The benefits of both schemes are shown through simulations.A method to handle data in ad-hoc networks using distributed hash tables (DHTs) is also presented. Moreover, we also present a physical layer security mechanism for multi-hop relaying. We also analyze the physical layer security mechanism for the cooperative MIMO scheme. This analysis shows that the cooperative MIMO scheme is more beneficial than co-located MIMO in terms of the information theoretic limits of the physical layer security.Nutzer mobiler Netzwerke fordern zunehmend höhere Datenraten von ihren Dienstleistern. Um diesem Bedarf gerecht zu werden, wurden verschiedene Signalverarbeitungsalgorithmen entwickelt. Dabei ist das "Multiple input multiple output" (MIMO)-Verfahren für die drahtlose Kommunikation eine der vielversprechendsten Techniken. Jedoch ist aufgrund bestimmter physikalischer Beschränkungen, wie zum Beispiel die Baugröße, die Verwendung von mehreren Antennen für viele Endgeräte nicht möglich. Dennoch können solche Ein-Antennen-Geräte durch den Einsatz kooperativer MIMO-Verfahren von den Vorteilen des MIMO-Prinzips profitieren. Dabei schließen sich naheliegende Knoten zusammen um ein sogenanntes virtuelles Antennen-Array zu bilden. Weiterhin können Knoten mit beschränktem Kommunikationsbereich durch mehrere Hops mit weiter entfernten Knoten kommunizieren. Allerdings stellt der Aufbau eines solchen Ad-hoc-Netzwerks mit kooperativen MIMO-Fähigkeiten aufgrund der dezentralen Natur und das Fehlen einer zentral-steuernden Einheit, wie einer Basisstation, eine große Herausforderung dar. Diese Arbeit befasst sich mit den Problemstellungen dieser Netzwerke und bietet verschiedene Lösungsansätze.Im ersten Teil dieser Arbeit werden analytisch in sich geschlossene Ausdrücke für ein kooperatives Relaying-System bezüglicher verschiedener Metriken, wie das Signal-Rausch-Verhältnis, die Symbolfehlerrate, die Bitfehlerrate und die Kapazität, hergeleitet. Dabei werden die "Amplify-and forward" und "Decode-and-forward" Relaying-Protokolle, sowie unterschiedliche Mehrantennen-Konfigurationen, wie "Single input single output" (SISO), "Single input multiple output" (SIMO) und MIMO betrachtet. Diese Ausdrücke zeigen die Bedeutung der Reduzierung der Hop-Anzahl in Mehr-Hop-Systemen, um eine höhere Leistung zu erzielen. Zudem werden die Auswirkungen verschiedener Antennen-Konfigurationen und Sendeleistungen auf die Anzahl der Hops analysiert.  Weiterhin wird der Einfluss von Synchronisationsfehlern auf das kooperative MIMO-Verfahren herausgestellt und daraus eine untere Grenze für das Signal-zu-Interferenz-und-Rausch-Verhältnis, sowie ein Ausdruck für die Bitfehlerrate bei hohem Signal-Rausch-Verhältnis entwickelt. Diese Zusammenhänge sollen Netzwerk-Designern helfen die Qualität des Services auch in den Worst-Case-Szenarien sicherzustellen. Im zweiten Teil der Arbeit werden einige innovative Algorithmen vorgestellt, die die Einrichtung und die Funktionsweise von Cluster-basierten Ad-hoc-Netzwerken, die kooperative Relays verwenden, erleichtern und verbessern. Darunter befinden sich ein Clustering-Algorithmus, der den Batteriestatus der Knoten berücksichtigt, um eine längere Lebensdauer des Netzwerks zu gewährleisten und ein Routing-Mechanismus, der auf den Einsatz in kooperativen MIMO Mehr-Hop-Systemen zugeschnitten ist. Die Vorteile beider Algorithmen werden durch Simulationen veranschaulicht. Eine Methode, die Daten in Ad-hoc-Netzwerken mit verteilten Hash-Tabellen behandelt wird ebenfalls vorgestellt. Darüber hinaus wird auch ein Sicherheitsmechanismus für die physikalische Schicht in Multi-Hop-Systemen und kooperativen MIMO-Systemen präsentiert. Eine Analyse zeigt, dass das kooperative MIMO-Verfahren deutliche Vorteile gegenüber dem konventionellen MIMO-Verfahren hinsichtlich der informationstheoretischen Grenzen der Sicherheit auf der physikalischen Schicht aufweist

ACUTA Journal of Telecommunications in Higher Education

In This Issue 5G\u27s Promise: 1,000 x Capacity, 1,000 x Challenges Higher-Speed WLANs About to Emerge State of the Residential Network 2013 LTE: The Next Wave of Wireless Evolution The 10 Most Costly Pitfalls of DAS Deployment and How to Avoid Them DAS on Campus: Solutions for Wireless Service Decision Criteria for Selecting a Wireless lntrusion Prevention System lnstitutional Excellence Award President\u27s Message From the CE

Contribution à la conception d'un système de radio impulsionnelle ultra large bande intelligent

Faced with an ever increasing demand of high data-rates and improved adaptability among existing systems, which inturn is resulting in spectrum scarcity, the development of new radio solutions becomes mandatory in order to answer the requirements of these emergent applications. Among the recent innovations in the field of wireless communications,ultra wideband (UWB) has generated significant interest. Impulse based UWB (IR-UWB) is one attractive way of realizing UWB systems, which is characterized by the transmission of sub nanoseconds UWB pulses, occupying a band width up to 7.5 GHz with extremely low power density. This large band width results in several captivating features such as low-complexity low-cost transceiver, ability to overlay existing narrowband systems, ample multipath diversity, and precise ranging at centimeter level due to extremely fine temporal resolution.In this PhD dissertation, we investigate some of the key elements in the realization of an intelligent time-hopping based IR-UWB system. Due to striking resemblance of IR-UWB inherent features with cognitive radio (CR) requirements, acognitive UWB based system is first studied. A CR in its simplest form can be described as a radio, which is aware ofits surroundings and adapts intelligently. As sensing the environment for the availability of resources and then consequently adapting radio’s internal parameters to exploit them opportunistically constitute the major blocks of any CR, we first focus on robust spectrum sensing algorithms and the design of adaptive UWB waveforms for realizing a cognitive UWB radio. The spectrum sensing module needs to function with minimum a-priori knowledge available about the operating characteristics and detect the primary users as quickly as possible. Keeping this in mind, we develop several spectrum sensing algorithms invoking recent results on the random matrix theory, which can provide efficient performance with a few number of samples. Next, we design the UWB waveform using a linear combination of Bsp lines with weight coefficients being optimized by genetic algorithms. This results in a UWB waveform that is spectrally efficient and at the same time adaptable to incorporate the cognitive radio requirements. In the 2nd part of this thesis, some research challenges related to signal processing in UWB systems, namely synchronization and dense multipath channel estimation are addressed. Several low-complexity non-data-aided (NDA) synchronization algorithms are proposed for BPSK and PSM modulations, exploiting either the orthogonality of UWB waveforms or theinherent cyclostationarity of IR-UWB signaling. Finally, we look into the channel estimation problem in UWB, whichis very demanding due to particular nature of UWB channels and at the same time very critical for the coherent Rake receivers. A method based on a joint maximum-likelihood (ML) and orthogonal subspace (OS) approaches is proposed which exhibits improved performance than both of these methods individually.Face à une demande sans cesse croissante de haut débit et d’adaptabilité des systèmes existants, qui à son tour se traduit par l’encombrement du spectre, le développement de nouvelles solutions dans le domaine des communications sans fil devient nécessaire afin de répondre aux exigences des applications émergentes. Parmi les innovations récentes dans ce domaine, l’ultra large bande (UWB) a suscité un vif intérêt. La radio impulsionnelle UWB (IR-UWB), qui est une solution intéressante pour réaliser des systèmes UWB, est caractérisée par la transmission des impulsions de très courte durée, occupant une largeur de bande allant jusqu’à 7,5 GHz, avec une densité spectrale de puissance extrêmement faible. Cette largeur de bande importante permet de réaliser plusieurs fonctionnalités intéressantes, telles que l’implémentation à faible complexité et à coût réduit, la possibilité de se superposer aux systèmes à bande étroite, la diversité spatiale et la localisation très précise de l’ordre centimétrique, en raison de la résolution temporelle très fine.Dans cette thèse, nous examinons certains éléments clés dans la réalisation d'un système IR-UWB intelligent. Nous avons tout d’abord proposé le concept de radio UWB cognitive à partir des similarités existantes entre l'IR-UWB et la radio cognitive. Dans sa définition la plus simple, un tel système est conscient de son environnement et s'y adapte intelligemment. Ainsi, nous avons tout d’abord focalisé notre recherché sur l’analyse de la disponibilité des ressources spectrales (spectrum sensing) et la conception d’une forme d’onde UWB adaptative, considérées comme deux étapes importantes dans la réalisation d'une radio cognitive UWB. Les algorithmes de spectrum sensing devraient fonctionner avec un minimum de connaissances a priori et détecter rapidement les utilisateurs primaires. Nous avons donc développé de tels algorithmes utilisant des résultats récents sur la théorie des matrices aléatoires, qui sont capables de fournir de bonnes performances, avec un petit nombre d'échantillons. Ensuite, nous avons proposé une méthode de conception de la forme d'onde UWB, vue comme une superposition de fonctions B-splines, dont les coefficients de pondération sont optimisés par des algorithmes génétiques. Il en résulte une forme d'onde UWB qui est spectralement efficace et peut s’adapter pour intégrer les contraintes liées à la radio cognitive. Dans la 2ème partie de cette thèse, nous nous sommes attaqués à deux autres problématiques importantes pour le fonctionnement des systèmes UWB, à savoir la synchronisation et l’estimation du canal UWB, qui est très dense en trajets multiples. Ainsi, nous avons proposé plusieurs algorithmes de synchronisation, de faible complexité et sans séquence d’apprentissage, pour les modulations BPSK et PSM, en exploitant l'orthogonalité des formes d'onde UWB ou la cyclostationnarité inhérente à la signalisation IR-UWB. Enfin, nous avons travaillé sur l'estimation du canal UWB, qui est un élément critique pour les récepteurs Rake cohérents. Ainsi, nous avons proposé une méthode d’estimation du canal basée sur une combinaison de deux approches complémentaires, le maximum de vraisemblance et la décomposition en sous-espaces orthogonaux,d’améliorer globalement les performances